Very high resolution bioclimatic zoning of Portuguese wine regions: present and future scenarios

Wine production is strongly affected by weather and climate and thus highly vulnerable to climate change. In Portugal, viticulture and wine production are an important economic activity. In the present study, current bioclimatic zoning in Portugal (1950–2000) and its projected changes under future climate conditions (2041–2070) are assessed through the analysis of an aggregated, categorized bioclimatic index (CatI) at a very high spatial resolution (near 1 km). CatI incorporates the most relevant bioclimatic characteristics of a given region, thus allowing the direct comparison between different regions. Future viticultural zoning is achieved using data from 13 climate model transient experiments following the A1B emission scenario. These data are downscaled using a two-step method of spatial pattern downscaling. This downscaling approach allows characterizing mesoclimatic influences on viticulture throughout Portugal. Results for the recent past depict the current spatial variability of Portuguese viticultural regions. Under future climate conditions, the current viticultural zoning is projected to undergo significant changes, which may represent important challenges for the Portuguese winemaking sector. The changes are quite robust across the different climate models. A lower bioclimatic diversity is also projected, resulting from a more homogeneous warm and dry climate in most of the wine regions. This will lead to changes in varietal suitability and wine characteristics of each region.

High-speed Keck spectroscopy of flares and oscillations in AE Aquarii

Using high-time-resolution (72 ms) spectroscopy of AE Aqr obtained with LRIS on Keck II we have determined the spectrum and spectral evolution of a small flare. Continuum and integrated line fluxes in the flare spectrum are measured, and the evolution of the flare is parametrized for future comparison with detailed models of the flares. We find that the velocities of the flaring components are consistent with those previously reported for AE Aqr by Welsh, Horne & Gomer and Horne. The characteristics of the 33-s oscillations are investigated: we derive the oscillation amplitude spectrum, and from that determine the spectrum of the heated regions on the rotating white dwarf. Blackbody fits to the major and minor pulse spectra and an analysis of the emission-line oscillation properties highlight the shortfalls in the simple hotspot model for the oscillations.

Derivation of an urban materials spectral library through emittance and reflectance spectroscopy

Recent advances in thermal infrared remote sensing include the increased availability of airborne hyperspectral imagers (such as the Hyperspectral Thermal Emission Spectrometer, HyTES, or the Telops HyperCam and the Specim aisaOWL), and it is planned that an increased number spectral bands in the long-wave infrared (LWIR) region will soon be measured from space at reasonably high spatial resolution (by imagers such as HyspIRI). Detailed LWIR emissivity spectra are required to best interpret the observations from such systems. This includes the highly heterogeneous urban environment, whose construction materials are not yet particularly well represented in spectral libraries. Here, we present a new online spectral library of urban construction materials including LWIR emissivity spectra of 74 samples of impervious surfaces derived using measurements made by a portable Fourier Transform InfraRed (FTIR) spectrometer. FTIR emissivity measurements need to be carefully made, else they are prone to a series of errors relating to instrumental setup and radiometric calibration, which here relies on external blackbody sources. The performance of the laboratory-based emissivity measurement approach applied here, that in future can also be deployed in the field (e.g. to examine urban materials in situ), is evaluated herein. Our spectral library also contains matching short-wave (VIS–SWIR) reflectance spectra observed for each urban sample. This allows us to examine which characteristic (LWIR and) spectral signatures may in future best allow for the identification and discrimination of the various urban construction materials, that often overlap with respect to their chemical/mineralogical constituents. Hyperspectral or even strongly multi-spectral LWIR information appears especially useful, given that many urban materials are composed of minerals exhibiting notable reststrahlen/absorption effects in this spectral region. The final spectra and interpretations are included in the London Urban Micromet data Archive (LUMA; http://LondonClimate.info/LUMA/SLUM.html).

Two-photon absorption of perylene derivatives: Interpreting the spectral structure

This work investigates the two-photon absorption spectrum of perylene tetracarboxylic derivatives using the white-light continuum Z-scan technique. Perylene derivatives present relatively high two-photon absorption cross-section, which makes them attractive for applications in photonics. Because of the spectral resolution of the white-light continuum Z-scan, we were able to observe a well defined structure in the two-photon absorption spectrum, composed by two distinct peaks. These peaks, as well as the resonant enhancement of the nonlinearity, were modeled using the sum-over-states approach considering a four-level energy diagram with two final two-photon states. The existence of such states was confirmed using the response function formalism within the DFT framework. (C) 2009 Elsevier B.V. All rights reserved.

High-resolution ice thickness and bed topography of a land-terminating section of the Greenland Ice Sheet, with links to GeoTIFFs and text files

We present ice thickness and bed topography maps with a high spatial resolution (250-500 m) of a land-terminating section of the Greenland Ice Sheet derived from ground-based and airborne radar surveys. The data have a total area of ~12 000 km^2 and cover the whole ablation area of the outlet glaciers of Isunnguata Sermia, Russell, Leverett, Ørkendalen and Isorlersuup up to the long-term mass balance equilibrium line altitude at ~1600 m above sea level. The bed topography shows highly variable subglacial trough systems, and the trough of Isunnguata Sermia Glacier is overdeepened and reaches an elevation of ~500 m below sea level. The ice surface is smooth and only reflects the bedrock topography in a subtle way, resulting in a highly variable ice thickness. The southern part of our study area consists of higher bed elevations compared to the northern part. The compiled data sets of ground-based and airborne radar surveys cover one of the most studied regions of the Greenland Ice Sheet and can be valuable for detailed studies of ice sheet dynamics and hydrology.

High resolution ultrastructural mapping of total calcium: electron spectroscopic imaging/electron energy loss spectroscopy analysis of a physically/chemically processed nerve-muscle preparation.

We report on a procedure for tissue preparation that combines thoroughly controlled physical and chemical treatments: quick-freezing and freeze-drying followed by fixation with OsO4 vapors and embedding by direct resin infiltration. Specimens of frog cutaneous pectoris muscle thus prepared were analyzed for total calcium using electron spectroscopic imaging/electron energy loss spectroscopy (ESI/EELS) approach. The preservation of the ultrastructure was excellent, with positive K/Na ratios revealed in the fibers by x-ray microanalysis. Clear, high-resolution EELS/ESI calcium signals were recorded from the lumen of terminal cisternae of the sarcoplasmic reticulum but not from longitudinal cisternae, as expected from previous studies carried out with different techniques. In many mitochondria, calcium was below detection whereas in others it was appreciable although at variable level. Within the motor nerve terminals, synaptic vesicles as well as some cisternae of the smooth endoplasmic reticulum yielded positive signals at variance with mitochondria, that were most often below detection. Taken as a whole, the present study reveals the potential of our experimental approach to map with high spatial resolution the total calcium within individual intracellular organelles identified by their established ultrastructure, but only where the element is present at high levels.

High-temperature sensitivity of long-period gratings in B-Ge codoped fiber

We report an investigation of thermal properties of long-period fiber gratings (LPFGs) of various periods fabricated in the conventional B-Ge codoped fiber. It has been found that the temperature sensitivity of the LPFGs produced in the B-Ge fiber can be significantly enhanced as compared with the standard telecom fiber. A total of 27.5-nm spectral shift was achieved from only 10 °C change in temperature for an LPFG with 240-μm period, demonstrating a first ever reported high sensitivity of 2.75 nm/°C. Such an LPFG may lead to high-efficiency and low-cost thermal/electrical tunable loss filters or sensors with extremely high-temperature resolution. The nonlinear thermal response of the supersensitive LPG was also reported and first explained.

High speed and high resolution demodulation system for hybrid WDM/FDM based fiber microstructure sensor network by using Fabry-Perot filter

Hybrid WDM/TDM enabled microstructure based optical fiber sensor network with large capacity is proposed. Assisted by Fabry-Perot filter, the demodulation system with high speed of 500Hz and high wavelength resolution less than 4.91pm is realized. © OSA 2015.

Atomic resolution studies of oxide superlattices and ultrathin films

The ability to grow ultrathin films layer-by-layer with well-defined epitaxial relationships has allowed research groups worldwide to grow a range of artificial films and superlattices, first for semiconductors, and now with oxides. In the oxides thin film research community, there have been concerted efforts recently to develop a number of epitaxial oxide systems grown on single crystal oxide substrates that display a wide variety of novel interfacial functionality, such as enhanced ferromagnetic ordering, increased charge carrier density, increased optical absorption, etc, at interfaces. The magnitude of these novel properties is dependent upon the structure of thin films, especially interface sharpness, intermixing, defects, and strain, layering sequence in the case of superlattices and the density of interfaces relative to the film thicknesses. To understand the relationship between the interfacial thin film oxide atomic structure and its properties, atomic scale characterization is required. Transmission electron microscopy (TEM) offers the ability to study interfaces of films at high resolution. Scanning transmission electron microscopy (STEM) allows for real space imaging of materials with directly interpretable atomic number contrast. Electron energy loss spectroscopy (EELS), together with STEM, can probe the local chemical composition as well as local electronic states of transition metals and oxygen. Both techniques have been significantly improved by aberration correctors, which reduce the probe size to 1 Å, or less. Aberration correctors have thus made it possible to resolve individual atomic columns, and possibly probe the electronic structure at atomic scales. Separately, using electron probe forming lenses, structural information such as the crystal structure, strain, lattice mismatches, and superlattice ordering can be measured by nanoarea electron diffraction (NED). The combination of STEM, EELS, and NED techniques allows us to gain a fundamental understanding of the properties of oxide superlattices and ultrathin films and their relationship with the corresponding atomic and electronic structure. In this dissertation, I use the aforementioned electron microscopy techniques to investigate several oxide superlattice and ultrathin film systems. The major findings are summarized below. These results were obtained with stringent specimen preparation methods that I developed for high resolution studies, which are described in Chapter 2. The essential materials background and description of electron microscopy techniques are given in Chapter 1 and 2. In a LaMnO3-SrMnO3 superlattice, we demonstrate the interface of LaMnO3-SrMnO3 is sharper than the SrMnO3-LaMnO3 interface. Extra spectral weights in EELS are confined to the sharp interface, whereas at the rougher interface, the extra states are either not present or are not confined to the interface. Both the structural and electronic asymmetries correspond to asymmetric magnetic ordering at low temperature. In a short period LaMnO3-SrTiO3 superlattice for optical applications, we discovered a modified band structure in SrTiO3 ultrathin films relative to thick films and a SrTiO3 substrate, due to charge leakage from LaMnO3 in SrTiO3. This was measured by chemical shifts of the Ti L and O K edges using atomic scale EELS. The interfacial sharpness of LaAlO3 films grown on SrTiO3 was investigated by the STEM/EELS technique together with electron diffraction. This interface, when prepared under specific conditions, is conductive with high carrier mobility. Several suggestions for the conductive interface have been proposed, including a polar catastrophe model, where a large built-in electric field in LaAlO3 films results in electron charge transfer into the SrTiO3 substrate. Other suggested possibilities include oxygen vacancies at the interface and/or oxygen vacancies in the substrate. The abruptness of the interface as well as extent of intermixing has not been thoroughly investigated at high resolution, even though this can strongly influence the electrical transport properties. We found clear evidence for cation intermixing through the LaAlO3-SrTiO3 interface with high spatial resolution EELS and STEM, which contributes to the conduction at the interface. We also found structural defects, such as misfit dislocations, which leads to increased intermixing over coherent interfaces.

SAFARI optical system architecture and design concept

SpicA FAR infrared Instrument, SAFARI, is one of the instruments planned for the SPICA mission. The SPICA mission is the next great leap forward in space-based far-infrared astronomy and will study the evolution of galaxies, stars and planetary systems. SPICA will utilize a deeply cooled 2.5m-class telescope, provided by European industry, to realize zodiacal background limited performance, and high spatial resolution. The instrument SAFARI is a cryogenic grating-based point source spectrometer working in the wavelength domain 34 to 230 μm, providing spectral resolving power from 300 to at least 2000. The instrument shall provide low and high resolution spectroscopy in four spectral bands. Low Resolution mode is the native instrument mode, while the high Resolution mode is achieved by means of a Martin-Pupplet interferometer. The optical system is all-reflective and consists of three main modules; an input optics module, followed by the Band and Mode Distributing Optics and the grating Modules. The instrument utilizes Nyquist sampled filled linear arrays of very sensitive TES detectors. The work presented in this paper describes the optical design architecture and design concept compatible with the current instrument performance and volume design drivers.

VUV spectral line emission measurements in the TCABR tokamak

The study of tokamak plasma light emissions in the vacuum ultraviolet (VUV) region is an important subject since many impurity spectral emissions are present in this region. These spectral emissions can be used to determine the plasma ion temperature and density from different species and spatial positions inside plasma according to their temperatures. We have analyzed VUV spectra from 500 Å to 3200 Å wavelength in the TCABR tokamak plasma including higher diffraction order emissions. There have been identified 37 first diffraction order emissions, resulting in 28 second diffraction order, 24 third diffraction order, and 7 fourth diffraction order lines. The emissions are from impurity species such as OII, OIII, OIV, OV, OVI, OVII, CII, CIII, CIV, NIII, NIV, and NV. All the spectra beyond 1900 Å are from higher diffraction order emissions, and possess much better spectral resolution. Each strong and isolated spectral line, as well as its higher diffraction order emissions suitable for plasma diagnostic is identified and discussed. Finally, an example of ion temperature determination using different diffraction order is presented.

The metal content of bulge field stars from FLAMES-GIRAFFE spectra - I. Stellar parameters and iron abundances

Aims. We determine the iron distribution function (IDF) for bulge field stars, in three different fields along the Galactic minor axis and at latitudes b = -4 degrees, b = -6 degrees, and b = -12 degrees. A fourth field including NGC 6553 is also included in the discussion. Methods. About 800 bulge field K giants were observed with the GIRAFFE spectrograph of FLAMES@VLT at spectral resolution R similar to 20 000. Several of them were observed again with UVES at R similar to 45 000 to insure the accuracy of the measurements. The LTE abundance analysis yielded stellar parameters and iron abundances that allowed us to construct an IDF for the bulge that, for the first time, is based on high-resolution spectroscopy for each individual star. Results. The IDF derived here is centered on solar metallicity, and extends from [Fe/H] similar to -1.5 to [Fe/H] similar to + 0.5. The distribution is asymmetric, with a sharper cutoff on the high-metallicity side, and it is narrower than previously measured. A variation in the mean metallicity along the bulge minor axis is clearly between b = -4 degrees and b = -6 degrees ([Fe/H] decreasing similar to by 0.6 dex per kpc). The field at b = -12 degrees. is consistent with the presence of a gradient, but its quantification is complicated by the higher disk/bulge fraction in this field. Conclusions. Our findings support a scenario in which both infall and outflow were important during the bulge formation, and then suggest the presence of a radial gradient, which poses some challenges to the scenario in which the bulge would result solely from the vertical heating of the bar.

The stellar content of obscured Galactic giant H II regions. VI. W51A

We present K-band spectra of newly born OB stars in the obscured Galactic giant H II region W51A and approximate to 0.8 '' angular resolution images in the J, H, and K(S)-bands. Four objects have been spectroscopically classified as O-type stars. The mean spectroscopic parallax of the four stars gives a distance of 2.0 +/- 0.3 kpc (error in the mean), significantly smaller than the radio recombination line kinematic value of 5.5 kpc or the values derived from maser proper motion observations (6-8 kpc). The number of Lyman continuum photons from the contribution of all massive stars (NLyc approximate to 1.5 x 10(50) s(-1)) is in good agreement with that inferred from radio recombination lines (NLyc = 1.3 x 10(50) s(-1)) after accounting for the smaller distance derived here. We present analysis of archival high angular resolution images (NAOS CONICA at VLT and T-ReCS at Gemini) of the compact region W51 IRS 2. The K(S)-band images resolve the infrared source IRS 2 indicating that it is a very young compact H II region. Sources IRS 2E was resolved into compact cluster (within 660 AU of projected distance) of three objects, but one of them is just bright extended emission. W51d1 and W51d2 were identified with compact clusters of three objects (maybe four in the case of W51d1) each one. Although IRS 2E is the brightest source in the K-band and at 12.6 mu m, it is not clearly associated with a radio continuum source. Our spectrum of IRS 2E shows, similar to previous work, strong emission in Br gamma and He I, as well as three forbidden emission lines of Fe III and emission lines of molecular hydrogen (H(2)) marking it as a massive young stellar object.

Remotely sensed estimates of vegetation structural characteristics in restored wetlands, Southern California

Traditional field sampling approaches for ecological studies of restored habitat can only cover small areas in detail, con be time consuming, and are often invasive and destructive. Spatially extensive and non-invasive remotely sensed data can make field sampling more focused and efficient. The objective of this work was to investigate the feasibility and accuracy of hand-held and airborne remotely sensed data to estimate vegetation structural parameters for an indicator plant species in a restored wetland. High spatial resolution, digital, multispectral camera images were captured from an aircraft over Sweetwater Marsh (San Diego County, California) during each growing season between 1992-1996. Field data were collected concurrently, which included plant heights, proportional ground cover and canopy architecture type, and spectral radiometer measurements. Spartina foliosa (Pacific cordgrass) is the indicator species for the restoration monitoring. A conceptual model summarizing the controls on the spectral reflectance properties of Pacific cordgrass was established. Empirical models were developed relating the stem length, density, and canopy architecture of cordgrass to normalized-difference-vegetation-index values. The most promising results were obtained from empirical estimates of total ground cover using image data that had been stratified into high, middle, and low marsh zones. As part of on-going restoration monitoring activities, this model is being used to provide maps of estimated vegetation cover.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.